Cancer is the second leading cause of death in the United States. Radiation therapy (RT), together with surgery and chemotherapy, is one of the most important modalities for cancer treatments. Patient safety is a paramount issue with radiation therapy. The safety concerns in radiation therapy have been recognized by many different national and international organizations including IAEA (International Atomic Energy Agency), ICRP (International Commission on Radiological Protection), NRC (Nuclear Regulatory Commission), WHO (World Health Organization), ASTRO (American Society for Radiation Oncology) and AAPM (American Association of Physicists in Medicine) in the past few decades. RT error was ranked as the #1 health technology hazard by ECRI (Emergency Care Research Institute). The field of radiation therapy as a whole has been attempting to improve patient safety over the past decades through the adoption of rigorous clinical workflows following the lessons learned from the previous incidents and following the guidelines published by the aforementioned organizations. However, as technologies become increasingly reliant on digital communication and workflows, the manual-auditing based safety measures continue to exhibit their limitations and antiquatedness. In this project, we propose to develop an automated health information technology (HIT) system to improve patient safety, treatment quality and working efficiency for radiation therapy. This system will continuously monitor errors and traces of inconsistencies in the patient data and documents in the clinical patient treatment systems, to make users aware of any patient safety issues. It is expected that the treatment quality will be improved by automatic performance of the standard-of-care quality checks and minimization of human errors in the clinical workflow. It is also expected that the working efficiency will be significantly improved due to the automatic safety and quality checks which when performed manually often account for approximately 50% of human worker workload. Over the past three years, we have been building such a HIT system and have demonstrated the clinical safety and quality significance and potential efficiency gains in our preliminary results. In this new project we plan to fundamentally overhaul our current efforts by making the computer-based safety and quality checks more accurate, responsive, user-friendly, powerful and fully automated. We also plan to integrate human factors into the design features, which were identified from the preliminary data, thereby maximizing the impacts of the system on safety and quality.